M. Riggs

A family of human phosphodiesterases homologous to the dunce learning and memory gene product of Drosophila melanogaster are potential targets for antidepressant drugs.

We have isolated cDNAs for four human genes (DPDE1 through DPDE4) closely related to the dnc learning and memory locus of Drosophila melanogaster. The deduced amino acid sequences of the Drosophila and human proteins have considerable homology, extending beyond the putative catalytic region to include two novel, highly conserved, upstream conserved regions (UCR1 and UCR2). The upstream conserved regions are located in the amino-terminal regions of the proteins and appear to be unique to these genes. Polymerase chain reaction analysis suggested that these genes encoded the only homologs of dnc in the human genome. Three of the four genes were expressed in Saccharomyces cerevisiae and shown to encode cyclic AMP-specific phosphodiesterases. The products of the expressed genes displayed the pattern of sensitivity to inhibitors expected for members of the type IV, cyclic AMP-specific class of phosphodiesterases. Each of the four genes demonstrated a distinctive pattern of expression in RNA from human cell lines.

Genome-wide copy number analysis of single cells

Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells in which information regarding genetic heterogeneity is lost. Here we present a protocol that allows for the genome-wide copy number analysis of single nuclei isolated from mixed populations of cells. Single-nucleus sequencing (SNS), combines flow sorting of single nuclei on the basis of DNA content and whole-genome amplification (WGA); this is followed by next-generation sequencing to quantize genomic intervals in a genome-wide manner. Multiplexing of single cells is discussed. In addition, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ∼3 d from flow cytometry to sequence-ready DNA libraries.

byr2, a Schizosaccharomyces pombe gene encoding a protein kinase capable of partial suppression of the ras1 mutant phenotype

Schizosaccharomyces pombe contains a single gene, ras1, which is a homolog of the mammalian RAS genes. ras1 is required for conjugation, sporulation, and normal cell shape. ras1 has been previously identified as ste5. We report here a gene we call byr2 that can encode a predicted protein kinase and can partially suppress defects in ras1 mutants. ras1 mutant strains expressing high levels of byr2 can sporulate competently but are still defective in conjugation and abnormally round. byr2 mutants are viable and have normal shape but are absolutely defective in conjugation and sporulation. byr2 is probably identical to ste8. In many respects, byr2 resembles the byr1 gene, another suppressor of the ras1 mutation, which has been identified previously as ste1. Our data indicate that if ras1, byr2, and byr1 act along the same pathway, then the site of action for byr2 is between the sites for ras1 and byr1.

Expression of three mammalian cDNAs that interfere with RAS function in Saccharomyces cerevisiae.

Saccharomyces cerevisiae strains expressing the activated RAS2Val19 gene or lacking both cAMP phosphodiesterase genes, PDE1 and PDE2, have impaired growth control and display an acute sensitivity to heat shock. We have isolated two classes of mammalian cDNAs from yeast expression libraries that suppress the heat shock-sensitive phenotype of RAS2Val19 strain. Members of the first class of cDNAs also suppress the heat shock-sensitive phenotype of pde1- pde2- strains and encode cAMP phosphodiesterases. Members of the second class fail to suppress the phenotype of pde1- pde2- strains and therefore are candidate cDNAs encoding proteins that interact with RAS proteins. We report the nucleotide sequence of three members of this class. Two of these cDNAs share considerable sequence similarity, but none are clearly similar to previously isolated genes.

Corrigendum: Genome-wide copy number analysis of single cells.

Nat. Protoc. 7, 1024–1041 (2012); published online 3 May 2012; corrected after print 24 February 2016 In the version of this article initially published, the units for the concentration of NaCl in the NST buffer described in the Reagent Setup section were incorrect. The correct unit should be mM. The error has been corrected in the HTML and PDF versions of the article.

Abstract 2989: Intra-tumor heterogeneity and clonal changes in the progression of DCIS to invasiveness: Combined tumor bulk and single cell analysis

INTRODUCTION: Ductal carcinoma in situ (DCIS) is a clonal intraductal proliferation of epithelial cells which acts as a non-obligate precursor of invasive breast cancer (IBC), yet the genetic events leading to the acquisition of invasive behavior remain unclear. We hypothesize that DCIS is composed of mosaics of genetically diverse tumor cell clones, and that the process of invasion is an evolutionary bottleneck. To test this hypothesis we performed a detailed characterization of the repertoire of genetic alterations and intra-tumor genetic heterogeneity in synchronously diagnosed DCIS and IBC using NextGen sequencing of bulk tumor and single cells. METHODS: DNA extracted from fresh frozen, microdissected DCIS, IBC and adjacent normal tissue was subjected to whole exome sequencing on an Illumina HiSeq2000. Reads were aligned to the reference human genome hg19. Single nucleotide variants (SNVs) were called by MuTect, and gene copy number alterations were determined using VarScan2. Single nuclei were isolated from 100μm serial sections microdissected to separate DCIS and IBC. Individual nuclei were FACS-sorted into a 96-well plate, lysed and whole genome amplified. Amplified DNA samples were barcoded, pooled and sequenced on a HiSeq2000. Single cell sequencing data were mapped to the reference genome and uniquely mapped reads were allocated into bins, normalized, segmented and CN values generated. RESULTS: In 6 cases of synchronous DCIS and IBC, a median of 41 and 47 non-synonymous mutations were found in each component, respectively. The somatic mutations identified in both DCIS and adjacent IBC components affected known driver breast cancer genes, including AKT1, PIK3CA, GATA3, MAP2K4 and TP53. Interestingly, we also found mutations restricted to either DCIS or IBC: ATRX (IBC-3); ALK and PKD2 (IBC-5); ESR1 (DCIS-5). The gene copy number profiles of matched DCIS and IBC were similar in all 6 pairs, however we also identified gene copy number alterations restricted either to DCIS or IBC: 1q gain (IBC-5); 3p and 3q losses (DCIS-6); 12p homozygous deletion (DCIS-4). Single cell sequencing of two cases (3 and 4) revealed that the majority of cells from both DCIS and IBC were derived from a common precursor lineage with shared copy number losses and gains. Both sets of DCIS-IBC pairs in these cases displayed elements of a subclonal structure with dominant clones alongside genetically diverse derivatives as well as genetic heterogeneity reflected in variable copy number alterations and non-modal clones. CONCLUSION: Synchronous DCIS and IBC share founder genetic events, but also harbor somatic genetic alterations restricted to either the DCIS or IBC components, demonstrating that although DCIS is a precursor of IBC, intra-tumor genetic heterogeneity is present at the DCIS stage. Changes in clonal composition likely take place in the progression from DCIS to IBC. Citation Format: Rita A. Sakr, Luciano G. Martelotto, Timour Baslan, Charlotte KY Ng, Jude Kendall, Linda Rodgers, Hilary Cox, Mike Riggs, Sean D9Itali, Asya Stepansky, Narciso Olvera, Tari A. King, Britta Weigelt, Jorge S. Reis-Filho, James Hicks. Intra-tumor heterogeneity and clonal changes in the progression of DCIS to invasiveness: Combined tumor bulk and single cell analysis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2989. doi:10.1158/1538-7445.AM2015-2989

Genome-Wide DNA Methylation Profiles of Breast Tumors Reveal Loci Associated with Relapse Risk.

Background:Breast cancer prognosis is used in determining the course of adjuvant therapy for patients. Clinical prognostic indices like the Nottingham Prognostic Index have poor specificity, overestimate the risk of disease recurrence and necessitate more specific and robust prognostic markers. Prognostic gene expression markers are already in clinical use and show improved decision support. Methylation of CpG islands, an important regulator of gene expression, is reported to be disregulated in tumors, thus making methylation markers an important alternative to gene expression markers. We present the results of a genome-wide study that explored loci whose methylation status was significantly associated with recurrence risk.Methods:We used 108 frozen primary breast cancer specimens with ten year follow-up and extensive clinical data including histopathological measurements to identify potential epigenetic markers associated with recurrence risk. Using a previously validated array based method (Kamalakaran et. al., Nucleic Acids Research, 2009) we performed genome-wide measurements of differential CpG island methylation covering over 150,000 loci. We evaluated each locus for its ability to stratify patients into good or poor prognosis groups depending on its methylation status. Statistical significance was established using permutation analysis with appropriate multiple testing corrections. Prognostic markers independent of histopathological factors (ER, PR, HER2, tumor size, grade, node status, age) were identified using multivariate Cox regression analysis.Results:The methylation status of several loci proximal to genes significantly stratified samples independent of other clinical variables. Demethylation of several loci were associated with poor prognosis including ADAMTS4 (Hazard Ratio = 17.5, p-value Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 4046.

Subtype Dependent Alterations of the DNA Methylation Landscape in Breast Cancer.

Background: The diversity of breast cancers at the clinical, histopathological and molecular level reflects variation in underlying biology and affects the clinical implications for patients. Gene expression studies have identified five breast cancer subtypes with distinct expression profiles – Luminal A, Luminal B, basal, ErbB2 enriched and Normal-Like. DNA methylation is an important regulator of gene expression that is also known to be deregulated in tumors. We set out to determine the relationship between DNA methylation and breast cancer subtypes in 108 breast cancer samples with previously determined expression subtypes.Methods: We performed high-throughput genome-wide scans of CpG methylation in 108 tumors and 11 normal tissues using our previously validated Methylation Oligonucleotide Microarray Analysis (MOMA) method [Kamalakaran, S et al. Nucleic Acids Research, 2009)]. We identified loci that were most varied across all tumors or had the most significant alterations and performed unsupervised hierarchical clustering on those loci. We then used a genetic algorithm based feature selection method to identify a subset of those loci that could cluster the sample set by expression subtype. We then characterized the loci contributing to subsetting and where possible, the relationship between methylation and gene expression.Results: Unsupervised hierarchical clustering using the 500 most differentially methylated loci across all tumors and 100 most significant altered loci between tumors and Normal tissues clustered the tumors into 3 major clusters – 82% of Cluster I belonged to Luminal Subtypes (22 Luminal A and 4 Luminal B), and 86% of Cluster II samples were of Basal or ErbB2+ subtypes. Cluster III did not show any expression subtype specific enrichment, but contained samples whose expression subtype was inconclusive with weak correlations to multiple expression subtypes. Interestingly, methylation loci that contributed to this clustering were not localized to CpG islands immediately upstream of genes, with 354 loci far from gene transcription start sites. These non-geneic loci did not show any significant regulatory potential based on cross-species conservation measures and no clear function could be assigned to these regions. The remaining 146 loci could be mapped to known genes. Gene expression microarray measurements were available for 79 of these geneic loci and 36 showed significant correlation of methylation to expression levels (p Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 1144.